Identification of cell-type-specific marker genes from co-expression patterns in tissue samples

Abstract

Motivation Marker genes, defined as genes that are expressed primarily in a single-cell type, can be identified from the single-cell transcriptome; however, such data are not always available for the many uses of marker genes, such as deconvolution of bulk tissue. Marker genes for a cell type, however, are highly correlated in bulk data, because their expression levels depend primarily on the proportion of that cell type in the samples. Therefore, when many tissue samples are analyzed, it is possible to identify these marker genes from the correlation pattern. Results To capitalize on this pattern, we develop a new algorithm to detect marker genes by combining published information about likely marker genes with bulk transcriptome data in the form of a semi-supervised algorithm. The algorithm then exploits the correlation structure of the bulk data to refine the published marker genes by adding or removing genes from the list. Availability and implementation We implement this method as an R package markerpen, hosted on CRAN (https://CRAN.R-project.org/package=markerpen). Supplementary information Supplementary data are available at Bioinformatics online.

Cell‐type‐specific metabolism in plants

“…For instance, tobacco guard cell enriched epidermal fragments display about 98% guard cell purity (Antunes et al., 2017; Daloso, Antunes, et al., 2015; Kopka et al., 1997; Kruse et al., 1989), while protocols for GCPs usually range between 98% and 99.5% in purity (Zhu, Jeon, et al., 2016). Purity can also be assessed by analyzing the expression of cell‐specific marker genes (Leonhardt et al., 2004) that are highly expressed in a specific cell type, and usually have low expression in other cell types (Qiu et al., 2021). For instance, NtRbcS‐T1 and NtMALD1 are specifically expressed in tobacco glandular trichomes (GTs) and can therefore be used as markers (Pottier et al., 2020).…”

Proteomic evidence of depression-associated astrocytic dysfunction in the human male olfactory bulb

“…Over enrichment of cell types based on DEPs was calculated by comparing published sets of gene lists and using fisher’s exact test to look for statistically significant overabundance. The list of genes for each major cell type was formed by taking the union of the markers from the McKenzie et al (2018) and Qiu et al (2021), with corresponding MarkerPen tool, plus genes selected to complete the cell type categories which were previously deemed insufficient, primary the OLs.…”

“…Samples were analyzed by nano Liquid Chromatography with tandem mass spectrometry (LC-MS/MS) by data dependent acquisition (DDA) using an Easy nLC 1200 coupled with a Q Exactive Plus mass spectrometer (Thermo Fisher Scientific). Details of nanoLC-MS/MS and the analyses are provided in the Supplementary Methods [18][19][20].…”

Isthmin-1 (Ism1) modulates renal branching morphogenesis and mesenchyme condensation during early kidney development

“…Co-expression analysis has been used, in both bulk-RNA sequencing and scRNA-seq. To examine the protein-protein interactions (PPI) or to predict the functions of uncharacterized ligands [31][32][33][34] . Here, 8 ligands including Sema3f, Vegfb, Fjx1, Sema3c, Ism1, Gdf11, Ntf3, Fgf9, were identified in the top 20 ligands co-expressed with Gdnf in both E10.5 and E11.5 NPCs (Fig.…”